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» Evolving hash functions by means of genetic programming
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CEC
2009
IEEE
14 years 2 months ago
Representation and structural biases in CGP
— An evolutionary algorithm automatically discovers suitable solutions to a problem, which may lie anywhere in a large search space of candidate solutions. In the case of Genetic...
Andrew J. Payne, Susan Stepney
GECCO
2006
Springer
124views Optimization» more  GECCO 2006»
13 years 11 months ago
On evolving buffer overflow attacks using genetic programming
In this work, we employed genetic programming to evolve a "white hat" attacker; that is to say, we evolve variants of an attack with the objective of providing better de...
Hilmi Günes Kayacik, Malcolm I. Heywood, A. N...
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
13 years 8 months ago
Genetic programming with polymorphic types and higher-order functions
This article introduces our new approach to program representation for genetic programming (GP). We replace the usual s-expression representation scheme by a strongly-typed ion-ba...
Franck Binard, Amy P. Felty
EUROGP
2004
Springer
129views Optimization» more  EUROGP 2004»
14 years 29 days ago
Evolution and Acquisition of Modules in Cartesian Genetic Programming
The paper presents for the first time automatic module acquisition and evolution within the graph based Cartesian Genetic Programming method. The method has been tested on a set of...
James Alfred Walker, Julian Francis Miller
GLOBECOM
2008
IEEE
13 years 7 months ago
On the Impact of Caching for High Performance Packet Classifiers
Hash functions have a space complexity of O(n) and a possible time complexity of O(1). Thus, packet classifiers exploit hashing to achieve packet classification in wire speed. Esp...
Harald Widiger, Andreas Tockhorn, Dirk Timmermann